Environmental health risk assessment of dioxin in foods at the two most severe dioxin hot spots in Vietnam

Background Bien Hoa and Da Nang airbases were bulk storages for Agent Orange during the Vietnam War and currently are the two most severe dioxin hot spots. Objectives This study assesses the health risk of exposure to dioxin through foods for local residents living in seven wards surrounding these airbases. Methods This study follows the Australian Environmental Health Risk Assessment Framework to assess the health risk of exposure to dioxin in foods. Forty-six pooled samples of commonly consumed local foods were collected and analyzed for dioxin/furans. A food frequency and Knowledge–Attitude–Practice survey was also undertaken at 1000 local households, various stakeholders were involved and related publications were reviewed. Results Total dioxin/furan concentrations in samples of local “high-risk” foods (e.g. free range chicken meat and eggs, ducks, freshwater fish, snail and beef) ranged from 3.8 pg TEQ/g to 95 pg TEQ/g, while in “low-risk” foods (e.g. caged chicken meat and eggs, seafoods, pork, leafy vegetables, fruits, and rice) concentrations ranged from 0.03 pg TEQ/g to 6.1 pg TEQ/g. Estimated daily intake of dioxin if people who did not consume local high risk foods ranged from 3.2 pg TEQ/kg bw/day to 6.2 pg TEQ/kg bw/day (Bien Hoa) and from 1.2 pg TEQ/kg bw/day to 4.3 pg TEQ/kg bw/day (Da Nang). Consumption of local high risk foods resulted in extremely high dioxin daily intakes (60.4–102.8 pg TEQ/kg bw/day in Bien Hoa; 27.0–148.0 pg TEQ/kg bw/day in Da Nang). Conclusions Consumption of local “high-risk” foods increases dioxin daily intakes far above the WHO recommended TDI (1–4 pg TEQ/kg bw/day). Practicing appropriate preventive measures is necessary to significantly reduce exposure and health risk.

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5–89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.

Sustainability at the Australian local government level: Is there room for Strategic Environmental Assessment (SEA)?

Recent calls in Australia have addressed the need for better integration of planning processes. The consequent effort made by government has been, and still is, reshaping the way urban and regional planning and sustainability are managed. Focusing on planning practices at the local and regional levels, we investigate how environmental sustainability is pursued from an institutional perspective. Specifically, we analyse the way that planning in Australian cities aims to achieve sustainable strategies and reflect on the relationship with ‘Strategic Environmental Assessment’. This paper has four goals. First, sustainable planning practices at the local and regional levels are analysed considering the legislative and organizational frameworks of each state. The goal is to identify through an analysis of planning documents how much discretion is given to local councils to address sustainable strategies. Second, we focus on two regional and four cities in Queensland, to outline strengths and weaknesses of current legislative and practical frameworks. We use analytical criteria from the SEA literature to investigate these plans in more detail. Third, we examine the relationship between strategic and statutory plans, to see how sustainability is actually implemented. Finally we compare emerging issues about sustainable planning in Australia with countries overseas with different planning and SEA traditions. Considering that SEA is evolving and there are considerable international experiences, we offer recommendations on how Australia might achieve a more integrated and sustainable approach to planning.

Compact features for birdcall retrieval from environmental acoustic recordings

Bioacoustic data can be used for monitoring animal species diversity. The deployment of acoustic sensors enables acoustic monitoring at large temporal and spatial scales. We describe a content-based birdcall retrieval algorithm for the exploration of large data bases of acoustic recordings. In the algorithm, an event-based searching scheme and compact features are developed. In detail, ridge events are detected from audio files using event detection on spectral ridges. Then event alignment is used to search through audio files to locate candidate instances. A similarity measure is then applied to dimension-reduced spectral ridge feature vectors. The event-based searching method processes a smaller list of instances for faster retrieval. The experimental results demonstrate that our features achieve better success rate than existing methods and the feature dimension is greatly reduced.

Assessing environmental inequalities in ambient air pollution across urban Australia

Identifying inequalities in air pollution levels across population groups can help address environmental justice concerns. We were interested in assessing these inequalities across major urban areas in Australia. We used a land-use regression model to predict ambient nitrogen dioxide (NO2) levels and sought the best socio-economic and population predictor variables. We used a generalised least squares model that accounted for spatial correlation in NO2 levels to examine the associations between the variables. We found that the best model included the index of economic resources (IER) score as a non-linear variable and the percentage of non-Indigenous persons as a linear variable. NO2 levels decreased with increasing IER scores (higher scores indicate less disadvantage) in almost all major urban areas, and NO2 also decreased slightly as the percentage of non-Indigenous persons increased. However, the magnitude of differences in NO2 levels was small and may not translate into substantive differences in health.

Statistical power calculation and sample size determination for environmental studies with data below detection limits

Power calculation and sample size determination are critical in designing environmental monitoring programs. The traditional approach based on comparing the mean values may become statistically inappropriate and even invalid when substantial proportions of the response values are below the detection limits or censored because strong distributional assumptions have to be made on the censored observations when implementing the traditional procedures. In this paper, we propose a quantile methodology that is robust to outliers and can also handle data with a substantial proportion of below-detection-limit observations without the need of imputing the censored values. As a demonstration, we applied the methods to a nutrient monitoring project, which is a part of the Perth Long-Term Ocean Outlet Monitoring Program. In this example, the sample size required by our quantile methodology is, in fact, smaller than that by the traditional t-test, illustrating the merit of our method.

Do stakeholders or social obligations drive corporate social and environmental responsibility reporting? Managerial views from a developing country

Purpose – The purpose of this study is to explore senior managers’ perception and motivations of corporate social and environmental responsibility (CSER) reporting in the context of a developing country, Bangladesh. Design/methodology/approach – In-depth semi-structured interviews were conducted with 25 senior managers of companies listed on the Dhaka Stock Exchange. Publicly available annual reports of these companies were also analysed. Findings – The results indicate that senior managers perceive CSER reporting as a social obligation. The study finds that the managers focus mostly on child labour, human resources/rights, responsible products/services, health education, sports and community engagement activities as part of the social obligations. Interviewees identify a lack of a regulatory framework along with socio-cultural and religious factors as contributing to the low level of disclosures. These findings suggest that CSER reporting is not merely stakeholder-driven, but rather country-specific social and environmental issues play an important role in relation to CSER reporting practices. Research limitations/implications – This paper contributes to engagement-based studies by focussing on CSER reporting practices in developing countries and are useful for academics, practitioners and policymakers in understanding the reasons behind CSER reporting in developing countries. Originality/value – This paper addresses a literature “gap” in the empirical study of CSER reporting in a developing country, such as Bangladesh. This study fills a gap in the existing literature to understand managers’ motivations for CSER reporting in a developing country context. Managerial perceptions on CSER issues are largely unexplored in developing countries.

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

Within-family outliers: Segregating alleles or environmental effects? A linkage analysis of height from 5815 sibling pairs

Most information in linkage analysis for quantitative traits comes from pairs of relatives that are phenotypically most discordant or concordant. Confounding this, within-family outliers from non-genetic causes may create false positives and negatives. We investigated the influence of within-family outliers empirically, using one of the largest genome-wide linkage scans for height. The subjects were drawn from Australian twin cohorts consisting of 8447 individuals in 2861 families, providing a total of 5815 possible pairs of siblings in sibships. A variance component linkage analysis was performed, either including or excluding the within-family outliers. Using the entire dataset, the largest LOD scores were on chromosome 15q (LOD 2.3) and 11q (1.5). Excluding within-family outliers increased the LOD score for most regions, but the LOD score on chromosome 15 decreased from 2.3 to 1.2, suggesting that the outliers may create false negatives and false positives, although rare alleles of large effect may also be an explanation. Several regions suggestive of linkage to height were found after removing the outliers, including 1q23.1 (2.0), 3q22.1 (1.9) and 5q32 (2.3). We conclude that the investigation of the effect of within-family outliers, which is usually neglected, should be a standard quality control measure in linkage analysis for complex traits and may reduce the noise for the search of common variants of modest effect size as well as help identify rare variants of large effect and clinical significance. We suggest that the effect of within-family outliers deserves further investigation via theoretical and simulation studies.

Genetic and environmental influences on migraine: a twin study across six countries

Migraine is a common neurovascular brain disorder that is manifested in recurrent episodes of disabling headache. The aim of the present study was to compare the prevalence and heritability of migraine across six of the countries that participate in GenomEUtwin project including a total number of 29,717 twin pairs. Migraine was assessed by questionnaires that differed between most countries. It was most prevalent in Danish and Dutch females (32% and 34%, respectively), whereas the lowest prevalence was found in the younger and older Finnish cohorts (13% and 10%, respectively). The estimated genetic variance (heritability) was significant and the same between sexes in all countries. Heritability ranged from 34% to 57%, with lowest estimates in Australia, and highest estimates in the older cohort of Finland, the Netherlands, and Denmark. There was some indication that part of the genetic variance was non-additive, but this was significant in Sweden only. In addition to genetic factors, environmental effects that are non-shared between members of a twin pair contributed to the liability of migraine. After migraine definitions are homogenized among the participating countries, the GenomEUtwin project will provide a powerful resource to identify the genes involved in migraine.

Structural and thermal properties of inorganic–organic montmorillonite: Implications for their potential environmental applications

Inorganic–organic clays (IOCs), clays intercalated with both organic cations such as cationic surfactants and inorganic cations such as metal hydroxy polycations have the properties of both organic and pillared clays, and thereby the ability to remove both inorganic and organic contaminants from water simultaneously. In this study, IOCs were synthesised using three different methods with different surfactant concentrations. Octadecyltrimethylammonium bromide (ODTMA) and hydroxy aluminium ([Al13O4 (OH)24(H2O)12]7+ or Al13) are used as the organic and inorganic modifiers (intercalation agents). According to the results, the interlayer distance, the surfactant loading amount and the Al/Si ratio of IOCs strictly depend on the intercalation method and the intercalation agent ratio. Interlayers of IOCs synthesised by intercalating ODTMA before Al13 and IOCs synthesised by simultaneous intercalation of ODTMA and Al13 were increased with increasing the ODTMA concentration used in the synthesis procedure and comparatively high loading amounts could be observed in them. In contrast, Al/Si decreased with increasing ODTMA concentration in these two types of IOCs. The results suggest that Al-pillars can be fixed within the interlayers by calcination and any increment in the amount of ODTMA used in the synthesis procedure did not affect the interlayer distance of the IOCs. Overall the study provides valuable insights into the structure and properties of the IOCs and their potential environmental applications.

Relationships between daily affect and pro-environmental behavior at work: The moderating role of pro-environmental attitude

Research in organizational psychology has increasingly focused on understanding the determinants of "green" employee behavior. The present study used a daily diary design to investigate relationships between employees' daily affect, pro-environmental attitude, as well as daily task-related pro-environmental behavior (i.e., the extent to which employees complete required work tasks in environmentally friendly ways), and daily proactive pro-environmental behavior (i.e., the extent to which employees show personal initiative when acting in environmentally friendly ways at work). Fifty-six employees working in small businesses completed a baseline survey and two daily surveys over ten workdays. Daily unactivated positive affect and pro-environmental attitude positively predicted daily task-related pro-environmental behavior. In addition, daily activated positive affect positively predicted daily proactive pro-environmental behavior among employees with a less positive pro-environmental attitude but not among employees with a more positive pro-environmental attitude. These findings suggest that fostering pro-environmental attitudes and, to some extent, positive affect among employees could help organizations to promote pro-environmental behavior in the workplace.

On the importance of pro-environmental organizational climate for employee green behavior

In their call to action, Ones and Dilchert(2012) discuss several possible individual and some contextual determinants of employee green behavior that await examination by industrial and organizational I–O) psychologists. Although these authors briefly mentioned organizational climate, specifically ethical climate, as a potentially relevant predictor of green behaviors, they mostly emphasized the role of individual difference characteristics and traditional job performance determinants such as knowledge, skills, abilities, and other person factors (KSAOs).